Dialysis resource allocation in critical care: the impact of the COVID-19 pandemic and the promise of big data analytics - Koraishy, Farrukh M.; Mallipattu, Sandeep K. (Frontiers in Nephrology, 2023)
The COVID-19 pandemic resulted in an unprecedented burden on intensive care units (ICUs). With increased demands and limited supply, critical care resources including dialysis machines became scarce, leading to value -based cost-effectiveness analysis and rationing of the resources to achieve the highest quality patient care. A high proportion of COVID-19 patients admitted to the ICU required dialysis resulting in a major burden on resources like dialysis machines, nursing staff, technicians and consumables like dialysis filters and solutions, and anticoagulation medications.Artificial intelligence (AI)-based big data analytics are now being utilized in multiple data-driven healthcare services including optimization of health system utilization. Numerous factors can impact dialysis resource allocation in the critically ill especially during public health emergencies, but currently the resource allocation is determined using a small number of traditional factors. Smart analytics that takes into account all the relevant healthcare information in the hospital system and patient outcomes can lead to improved resource allocation, cost-effectiveness and quality of care.In this review, we discuss dialysis resource utilization in critical care, the impact of the COVID-19 pandemic and how AI can improve resource utilization in future public health emergencies. Research in this area should be an important priority.